两种激光模型的量子起伏

本文研究激光理论中使用的两种模型（Ｈａｋｅｎ模型和Ｌｏｕｉｓｅｌｌ模型）的量子起伏。在原子变量绝热消除条件下，研究两种模型在阈值附近或远高于阈值时，输出光谱振幅的起伏，并给出两种模型相互逼近的条件。     

激光模型中输出光谱的振幅起伏

本文研究激光理论中使用的两种模型（Haken模型和Louisell模型）的量子起伏。在Haken模型中，激光介质由两能级原子组成，而Louisell模型中是由三能级原子组成。在原子变量绝热消除条件下，研究两种模型在阈值附近或远高于阈值时，输出光谱的振福起伏，并给出两种模型相互逼近的条件。     

分形维数、临界阈值、逾渗阈值的计算

文章采用改进的RSNG模型(Random Successive Nucleation Growth Model)，总结了三种计算聚集体分形维数的方法；运用逼近法确定分形向均匀结构的临界阈值；使用两种方法计算了在三种近邻条件下的逾渗阈值。计算结果表明：计算分形维数三种方法的结果相同；而计算逾渗阈值两种方法的结果完全一致。     

起伏地表条件下坐标变换的瑞雷波场正演模拟

利用高精度交错网格有限差分技术模拟起伏地表条件下的瑞雷波全波场正演,通过坐标变换的方式实现起伏地表自由边界条件.与一个已知模型结果对比,验证该算法的可行性与正确性,并通过在一个地表起伏的均匀介质中瑞雷波的模拟,结果说明了该方法的适应性.两个模型的模拟结果均表明,即使是地下室均一的介质,但由于地表起伏的存在不可避免地会产生波型的转换与能量的再分配,瑞雷波波场必然受到一定的影响.     

具有Holling功能性反应的捕食-食饵两种群同时捕获模型分析

研究一类具有Holling功能性反应的捕食—食饵两种群同时捕获模型,增加捕获项,推广了文献已有的功能性反应的捕食—食饵两种群模型结果,得到了平衡点稳定的阈值,从生态学的意义上得到了两种群持续生存的充分条件.     

界面量子起伏对铁电超晶格介电性质的影响

应用平均场理论，在横场伊辛模型的框架内，研究了界面量子起伏对铁电超晶格介电性质的影响。得到界面的量子起伏会导致铁电超晶格的介电极化率的升高。     

基于小波阈值去噪的改进方案

在D.L.Dohono提出的软、硬阈值去噪方法的基础上,提出了两种新的阈值函数,并对小波阈值的去噪算法进行仿真实验研究。首先分析软、硬阈值去噪法及最新的阈值改进算法,在此基础上提出两种改进小波阈值去噪算法,然后用提到的各种小波阈值去噪算法对指定图像进行去噪仿真研究,最后基于实验结果进行对比分析。新阈值函数在图像去噪方面要优于传统的软、硬阈值函数。能更好的保留原始图像信息,提高峰值信噪比并降低均方误差。     

具有非线性感染力传染病模型中的阈值分析

基于无尺度网络的传染病动力学模型被广泛研究,考虑到出生和死亡对传染病动力学的重要影响,对一类SIS模型进行了改进。主要研究无尺度网络中非线性感染力对传染病阈值的影响,讨论了在几种不同的非线性感染力下的传染病阈值。     

利用橡皮泥制作起伏地表物理模型进行直流电法实验

目前室内直流电法实验大都在水槽里进行,所以要想得到起伏地表的实验结果是很难的。尽管土和沙子可以制作成起伏地表模型,但是都有各自的优缺点。采用橡皮泥制作模型实现了起伏地表的实验,为今后在室内进行直流电法实验找到了一种简单易行的方法。     

基于和声搜索算法的图像阈值寻优算法

针对最大类间方差法在图像分割时产生的阈值会引起过分割的缺点,提出一种基于和声搜索算法的图像阈值寻优算法。算法将苹果图像预处理、计算图像目标和背景两类间方差作为和声搜索算法的目标函数,通过和声搜索算法寻找最优分割阈值,选取6种不同光照条件下的苹果图像进行阈值寻优实验。结果表明,采用基于和声搜索算法的图像阈值寻优算法较最大类间方差法和基于混合蛙跳算法的图像阈值寻优算法具有较好的图像阈值寻优能力。     

基于非线性组合模型对石油价格的预测

鉴于石油在国民经济中的重要地位及其对金融市场的重要影响,提出新的非线性组合预测模型:HP滤波-AR模型-ARMA模型,使用HP滤波将原序列分解成两部分即周期性波动序列和趋势要素序列。根据两个序列的不同性质,对趋势要素序列建立AR模型,然后建立随机周期性波动序列,对随机周期性波动序列建立ARMA模型。将两个预测值之和与原序列比较,同时将该模型与其他模型进行对比。对比结果表明,预测精度高于其他模型。     

新能源行业收益率波动的动态特征分析

股票市场上收益率的波动随着时间的不同会有很大的变化,与传统计量方法相比, ARCH模型能够更好的刻画这种变化的特点。文章以新能源行业为例,选取该行业具有代表性的27支股票从2008年11月12日~2014年12月12日共1457个日收益率数据,运用ARCH模型族对其波动性进行定量与定性的分析。结果显示,新能源行业日收益率具有明显的高阶ARCH效应、波动聚集性、尖峰厚尾、杠杆效应和信息不对称的特点,且条件异方差的波动显著地影响日收益率,其中EGARCH模型在反映该行业日收益率波动性方面优于其他模型。     

基于神经网络的透气性状态预测

针对烧结过程的时变、强非线性等特点,基于神经网络和粒子群优化算法,提出一种预测透气性状态的集成方法.采用神经网络分别建立透气性预测模型,采用粒子群优化算法对神经网络进行训练,提高预测模型的实时性;进而借助模糊分类器将预测子模型实现有机融合.最后实际运行结果表明,提出的集成模型具有较高的预测精度和较强的自学习能力,并且在工况波动严重的情况下,仍然具有好的预测效果.     

EVA based model to estimate the Chinese listed company''s intrinsic value

This article is based on traditionally intrinsic value assessment model. We employed the assumption on the differences in future increase rates of companies, taking into account of the expected Economic Value Added (EVA) discount and the capital investment, to establish a high increase model, a two-stage EVA discount model and a three-stage EVA discount model for the intrinsic value assessment. Those models eliminate the great fluctuation of free cash flow in calculating the capital expenditure by setting aside the cash flow of the company's investment in the year and considering only the capital cost. This method needs only to assess the EVA flow in different year in probing the intrinsic value of a company, thus give more consistent conclusion than conventional methods.     

基于证券市场的套利模式分析

针对证券市场中跨期套利的基本行为,在套利定价理论、因素模型理论的基础上,建立了两种适用于证券市场的套利模式。对两种模式的构建进行了详细的分析与研究。对结果进行试验验证,证明了该套利模式的可行性。     

AR(p)与指数平滑组合预测算法

本文提出一种对铜铳品位进行预测的新方法，以采集的现场数据为基础，采用系统辩识动态地建立了AR(p)模型与三次指数平滑模型，AR（p)模型要求数据对象是平衡时间序列，而三次指数平滑型的数据对象具有随机性，考虑到铜锍品位的波动性，本文将二模型按最小二乘法原理，以组合预测误差平方和为目标函数，通过使误差平方和极小化来确定两种预测方法的优化，建立了一种新的组合模型，在三种模型中其预测误差最小。     

A Short Note on Interpretation in the Dual Change Score Model

The latent change score framework allows for estimating a variety of univariate trajectory models, such as the no change, linear change, exponential forms of change, as well as multivariate trajectory models that allow for coupling between two or more constructs. A particularly attractive feature of these models is that it is easy to decompose and interpret aspects of change. One particularly flexible model, the dual change score model, has two components of change: a proportional change component that depends on scores at the previous time point, and a constant change component that is additive. We demonstrate through simulation and an empirical example that in a correctly specified model, the correlation between the proportional change parameter and the mean of the constant change component can approach either ?1 or 1, thus complicating interpretation. We provide recommendations and code to aid researchers’ ability to diagnose this issue in their own data.     

Survival analysis for Hispanic ELL students’ access to postsecondary schools: discrete model or Cox regression?

Survival analysis is an advanced statistical method to investigate the occurrence and the timing of an important event such as school access, dropout, and graduation in a longitudinal framework. The aim of our study is to provide practical guidelines for empirical researchers in choosing an appropriate survival analysis model. For this goal, this study chose two major survival analytical models of a discrete-time hazard model and a Cox regression model and compared analytical outcomes considering time metrics, as well as sample sizes and censoring proportions. In the analytical model, the combined specifications of varying factors using two models were adopted to analyse the Educational Longitudinal Study of 2002. We chose the college access of Hispanic English Language Learners to understand the importance of adopting a proper survival model to examine the educational outcome in the educational context. Importantly, we considered the hazard probability for the target event in the model specification which is a fundamental yet often neglected component of survival analysis. We recommended discrete models for the cases with a smaller number of time points, larger time metrics, larger sample size, and smaller proportions of censored observations.     

The Properties and the Nature of Light: The Study of Newton’s Work and the Teaching of Optics

The history of science shows that for each scientific issue there may be more than one models that are simultaneously accepted by the scientific community. One such case concerns the wave and corpuscular models of light. Newton claimed that he had proved some properties of light based on a set of minimal assumptions, without any commitments to any one of the two models. This set of assumptions constitutes the geometrical model of light as a set of rays propagating in space. We discuss this model and the historical reasons for which it had the head-primacy amongst the relevant models. We argue that this model is indispensable in structuring the curriculum in Optics and attempt to validate it epistemologically. Finally, we discuss an approach for alleviating the implicit assumptions that students make on the nature of light and the subsequent interference of geometrical optics in teaching the properties of light related to its wave-like nature.